COVID-19: a need for real-time monitoring of weekly excess deaths

Leon, David A.; Shkolnikov, Vladimir M.; Smeeth, Liam; Magnus, Per; Pechholdová, Markéta; Jarvis, Christopher I

doi:10.1016/s0140-6736(20)30933-8

Cited by 221 publications

(236 citation statements)

References 2 publications

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“…In order to monitor and foresee the plausible progress of the ongoing COVID-19 pandemic, estimation of SI, CFR and R 0 is of prime importance, 5 and daily deaths, and growth rate of COVID-19 cases also display importance in gaging the scale of the pandemic across time and space, and in framing policies and procedures. 6,7 The dynamics of COVID-19 epidemic in Indian states with interventions was characterized by subexponential growth, which around 11 April 2020, deviated from the exponential growth of potential case numbers without interventions. Despite heterogeneities in socio-economic status and healthcare systems across Indian population, 2 similar growth patterns of COVID-19 among the states considered in the current study imply the effectiveness of the outbreak interventions.…”

Section: Discussionmentioning

confidence: 99%

Phasic containment of COVID-19 in substantially affected states of India

Mandal¹,

Mandal

2020

Preprint

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The spread of COVID-19 epidemic in some highly-impacted Indian states displayed a characteristic subexponential growth projected up to 3 May 2020, as a consequence of lockdown strategies, in addition to improvement of reproduction number (R), serial interval, and daily growth rate, but not case fatality rate (CFR). The effect of COVID-19 containment was more prominent in second phase of lockdown with declining R, which was still >1, suggesting the requirement of sustained interventions for effective containment of COVID-19 pandemic in Indian context.

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Section: Discussionmentioning

confidence: 99%

Phasic containment of COVID-19 in substantially affected states of India

Mandal¹,

Mandal

2020

Preprint

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“…Such data are still largely lacking in the literature. Excess mortality rates should best be calculated for both sexes and for each 5-years age range separately (Leon et al, 2020). First data have just now been reported: In March/April, the care sector of England and Wales alone has seen 20 000 excess deaths over the figures of previous years.…”

Section: Excess Mortalitymentioning

confidence: 99%

COVID‐19: test, trace and isolate‐new epidemiological data

Brüssow

2020

Environmental Microbiology

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Summary In the absence of an efficient drug treatment or a vaccine, the control of the COVID‐19 pandemic relies on classic infection control measures. Since these means are socially disruptive and come with substantial economic loss for societies, a better knowledge of the epidemiology of the new coronavirus epidemic is crucial to achieve control at a sustainable cost and within tolerable restrictions of civil rights.

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“…The epidemic in the United States will have an important impact on the global economy and politics. It is fundamental to make relatively accurate estimates of this pandemic for preventing and controlling COVID-19 in the United States 2,3 , wherein the transmission rate (TR), infection fatality rate (IFR) are key indicators 4 .…”

Section: Introductionmentioning

confidence: 99%

Estimating Unreported COVID-19 Cases in the United States Based on the tvSIRu Model

Liu¹,

Hu²,

Bao³

et al. 2020

Preprint

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BackgroundThe potential unreported infection may impair and mislead policymaking for COVID-19，and the contemporary spread of COVID-19 varies in different counties of the United States. It is necessary to estimate the cases that may be underestimated based on county-level data to take better countermeasures against COVID-19. We suggested taking time-varying SIR models with unreported infection rates (UIR)to estimate the factual COVID-19 cases in the United States.MethodsSIR integrated with unreported infection rates (SIRu) of fixed time effect and SIR with time-varying parameters (tvSIRu)were applied to estimate and compare the value of transmission rate(TR), UIR, and infection fatality rate (IFR) based on US county-level COVID-19 data. ResultsBased on US county-level COVID-19 data from January 22 (T1) to August 20 (T212) in 2020, SIRu was first tested and verified by a general OLS regression. The further regression of SIRu at the country-level showed that the average values of TR, UIR, and IFR were 0.034,19.5, 0.51% respectively. The range of TR, UIR, IFR of all states ranged were 0.007-0.157 (mean=0.048) ,7.31-185.6 (mean=38.89), and 0.04%-2.22% (mean=0.22%). Among time-varying transmission rate equations, the power function showed better fitness, which indicated a decline in TR decreasing from 227.58 (T1) to 0.022 (T212). The general equation of tvSIRu showed that both the UIR and IFR were gradually increasing, wherein, the UIR has an estimate of 9.1(95%CI = 5.7-14.0), and IFR was 0.70% (0.52%-0.95%) at T212.InterpretationDespite the decline in TR and IFR, the UIR of the United States is still on the rise, which had been supposed to decrease with sufficient tests or improved countersues. The US medical system may be largely affected by severe cases in the rapid spread of COVDI-19.

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COVID-19: a need for real-time monitoring of weekly excess deaths

Cited by 221 publications

References 2 publications

Phasic containment of COVID-19 in substantially affected states of India

Phasic containment of COVID-19 in substantially affected states of India

COVID‐19: test, trace and isolate‐new epidemiological data

Estimating Unreported COVID-19 Cases in the United States Based on the tvSIRu Model

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